**The Recovery from Sulfur Starvation Is Independent from the mRNA Degradation Initiation Enzyme PARN in Arabidopsis**

### **Laura Armbruster, Veli Vural Uslu, Markus Wirtz and Rüdiger Hell \***

Centre for Organismal Studies, Heidelberg University, 69120 Heidelberg, Baden-Württemberg, Germany; laura.armbruster@cos.uni-heidelberg.de (L.A.); veli.uslu@cos.uni-heidelberg.de (V.V.U.); markus.wirtz@cos.uni-heidelberg.de (M.W.)

**\*** Correspondence: ruediger.hell@cos.uni-heidelberg.de; Tel.: +49-6221-54-6284

Received: 26 August 2019; Accepted: 26 September 2019; Published: 27 September 2019

**Abstract:** When plants are exposed to sulfur limitation, they upregulate the sulfate assimilation pathway at the expense of growth-promoting measures. Upon cessation of the stress, however, protective measures are deactivated, and growth is restored. In accordance with these findings, transcripts of sulfur-deficiency marker genes are rapidly degraded when starved plants are resupplied with sulfur. Yet it remains unclear which enzymes are responsible for the degradation of transcripts during the recovery from starvation. In eukaryotes, mRNA decay is often initiated by the cleavage of poly(A) tails via deadenylases. As mutations in the poly(A) ribonuclease PARN have been linked to altered abiotic stress responses in *Arabidopsis thaliana*, we investigated the role of PARN in the recovery from sulfur starvation. Despite the presence of putative PARN-recruiting AU-rich elements in sulfur-responsive transcripts, sulfur-depleted PARN hypomorphic mutants were able to reset their transcriptome to pre-starvation conditions just as readily as wildtype plants. Currently, the subcellular localization of PARN is disputed, with studies reporting both nuclear and cytosolic localization. We detected PARN in cytoplasmic speckles and reconciled the diverging views in literature by identifying two PARN splice variants whose predicted localization is in agreement with those observations.

**Keywords:** AGS1; AHG2; sulfur starvation; PARN; recovery; sulfate transporters; sulfate resupply; mRNA degradation; rapid recovery downregulation

### **1. Introduction**

Sulfur is one of six essential macronutrients plants absorb from the soil in large quantities to sustain growth and survival [1]. In the last decade, insufficient sulfate nutrition has been reported with increasing frequency in widely cultivated crops such as wheat, soybean and rapeseed [2–4]. Since prolonged sulfur depletion results in severe stunting and impaired resistance to biotic stress, this translates into significant losses in crop yield [5,6]. Understanding the mechanisms by which plants respond to and recover from sulfur deficiency is an essential step towards improving agricultural productivity.

Plants adapt to sulfur depletion by upregulating the expression of genes involved in sulfate uptake and reduction [6]. Additionally, the expression of negative regulators of glucosinolate biosynthesis is induced to prioritize sulfur usage for primary metabolism [7]. The reverse processes by which sulfur-deficient plants reshape their transcriptome upon sulfur resupply are, however, only poorly understood.

In resupply studies, Bielecka and coworkers identified so-called genuine sulfur-responsive transcripts that directly reflect the sulfur status of *Arabidopsis thaliana*. Most (30 out of 35) of those transcripts accumulate upon sulfur starvation and display rapid decay rates in the first hours after the resupply of the macronutrient [8]. Adopting an exponential decay model, the average half-life of those starvation-induced transcripts can be determined to amount to 2.3 hours during the recovery phase [8]. This is considerably shorter than the mean mRNA half-life of 5.9 hours measured in global studies of Arabidopsis mRNA stability under standard growth conditions [9,10]. Taken together, these findings suggest that during the recovery from sulfur limitation, the transcriptome is cleared of starvation-responsive mRNAs by active degradation rather than the regular turnover of transcripts. The clearance of stress-induced transcripts is also required for the recovery from high-light stress. In this context, the term "rapid recovery downregulation" has been coined. It describes the quick return of transcript abundance to pre-stress levels upon recovery [11]. Yet for both sulfur starvation and excess-light stress, it remains unclear which enzymes are mediating the targeted degradation of mRNAs upon recovery.

In plants, a set of endonucleases, decapping enzymes and deadenylases govern the degradation of mRNA. While endonucleases cleave phosphodiester bonds within transcripts, decapping enzymes and deadenylases remove the methylguanine cap and the stabilizing poly(A) tail from the 5 and 3 ends of mRNAs [12–15]. The aforementioned enzymes are candidates to initiate the degradation of transcripts during the recovery from sulfur starvation. In this study, we focus on the role of the poly(A)-specific ribonuclease (*At*PARN) for the following reasons:

Unlike in *Schizosaccharomyces pombe* and *Caenorhabditis elegans*, PARN is essential for embryogenesis in *Arabidopsis thaliana*, indicating a unique role of PARN-mediated mRNA decay in higher plants [16]. *At*PARN hypomorphic mutants (*parn*) display diminished growth accompanied by an increased resistance to bacterial pathogens and a decreased tolerance towards osmotic stress [17–20]. These altered stress responses can be attributed to the accumulation of the phytohormone abscisic acid (ABA) in *parn* mutants, resulting from the disturbed equilibrium between polyadenylation and the deadenylation of specific stress-related transcripts [17,18,20,21]. Remarkably, sulfate and cysteine have recently been shown to trigger ABA biosynthesis in plants. Hence, the elevated ABA levels observed in *parn* mutants could be the result of increased sulfate assimilation [22,23].

Mammalian PARNs have been observed to preferentially degrade the poly(A) tails of transcripts harboring AU-rich signal elements (AREs) in their 3 untranslated regions (UTRs). AREs range from 40 to 150 nucleotides in length and typically contain one or more AUUUA motifs within AU-rich sequence stretches [24–26]. The close evolutionary relationship between mammalian PARNs and *At*PARN suggests that *At*PARN might be recruited by AREs as well. In line with this assumption, *At*PARN was shown to target a specific subset of mRNAs rather than the entire mRNA population [16].

Here, we report that the AUUUA motif is present in the 3- UTRs of many transcripts induced by sulfur depletion, including the *O*-acetylserine cluster genes *SDI1*, *GGCT* and *SHM7* [27] as well as the high-affinity sulfur transporter genes *SULTR1;1* and *SULTR1;2*. This finding makes *At*PARN a potential candidate for the regulation of active mRNA degradation during the recovery from sulfur depletion.

However, analysis of transcript stability by qRT-PCR in PARN hypomorphic mutants demonstrates that PARN is not required for the targeted degradation of sulfur deficiency-induced transcripts in Arabidopsis. To understand the biological role of PARN, we determine the subcellular localization of PARN and its antagonist, the poly(A) polymerase AGS1. To this end we image stable Arabidopsis lines expressing PARN-GFP or AGS1-GFP fusions under the control of the respective endogenous promoters. Unlike the predominantly nuclear localized AGS1, PARN accumulates in cytoplasmic speckles. So far, PARN has been observed to localize to processing bodies (p-bodies) when transiently expressed under the control of the 35S promoter in tobacco leaves [28]. This, however, contradicts earlier PARN localization studies in onion epidermal peels reporting a nuclear–cytoplasmic localization [16,29]. By detecting two PARN splice variants, which were bioinformatically predicted to localize to different cellular compartments, we offer an explanation for the diverging accounts of PARN localization in the literature.

### **2. Results**

Upon recovery from sulfur starvation, transcripts of many stress-induced genes are rapidly degraded. We reasoned that recognition signals embedded in those transcripts might provide specificity to the process and link them to the active degradation machinery of plants. AREs in the 3- UTRs of transcripts have been known to target mammalian mRNAs for rapid degradation by recruiting the deadenylase PARN [30]. This observation prompted us to search for AREs in the 3- UTRs of transcripts upregulated upon sulfur starvation.

### *2.1. The Sulfur-Responsive Transcripts SULTR1;1, SULTR1;2, SDI1, SHM7 and GGCT Contain ARE Sites*

We could identify AREs in many transcripts that are involved in sulfur metabolism and are upregulated upon sulfur starvation, including the *O*-acetylserine dependent cluster genes *SDI1*, *GGCT* and *SHM7* [27] as well as the high-affinity sulfate transporter genes *SULTR1;1* and *SULTR1;2* (Figure 1). In contrast, transcripts that were not induced upon sulfur starvation but are involved in sulfur metabolism did in many cases lack AREs (e.g., *SHM1-4*, *SERAT 2;1* and *SERAT2;2*, *OAS-TL A* and *SIR*). There was, however, no significant difference in ARE frequency between sulfur metabolism-related and general transcripts. Given the broad presence in mRNAs encoding for the sulfur metabolism pathway, we hypothesized that the degradation of sulfur-responsive transcripts upon the recovery from starvation might depend on PARN.

**Figure 1.** Plants regulate the transcription of genes involved in sulfate assimilation and glucosinolate biosynthesis in response to sulfur supply. When plants are exposed to sulfur limitation, they upregulate the expression of genes involved in sulfate uptake and assimilation. Simultaneously, the expression of genes implicated in the synthesis of sulfur-containing secondary metabolites is downregulated to prioritize sulfate usage for primary metabolites. In this scheme of plant sulfate metabolism, the transcript levels of genes (italics) encoding for enzymes mediating sulfate assimilation (bold) are indicated by a color code. Red and blue represent significant (p < 0.05; ≥2-fold) up- and downregulations under sulfur limitation. White represents no significant change in comparison to full nutrient supply. Many sulfur responsive transcripts harbor AU-rich signal elements (AREs) in their 3 untranslated regions (UTRs). The number of AREs found in each 3- UTR is indicated next to the asterisk. (Transcript data from [31]).

### *2.2. The Degradation of Sulfur Metabolism-Related Transcripts Is Independent of AtPARN*

To determine whether PARN degrades starvation-induced transcripts after sulfur resupply in *Arabidopsis thaliana*, we depleted six-week-old hydroponically grown *parn, parn-ags1* and wildtype plants of sulfur. After two weeks of starvation (0 μM sulfur), the plants were transferred back to <sup>1</sup> 2 Hoagland medium (500 μM sulfur) for three hours to allow recovery. Subsequently, the transcript levels of the sulfur-starvation marker genes *SULTR1;1*, *SULTR1;2*, *SDI1*, *SHM7* and *GGCT* were assessed via qRT-PCR in roots (Figure 2).

**Figure 2.** *At*PARN is not required for the degradation of sulfur starvation-induced transcripts upon the resupply of the macronutrient. Relative transcript levels of *SULTR1;1* (**a**), *SULTR1;2* (**b**), *SHM7* (**c**), *SDI1* (**d**) and *GGCT* (**e**) upon regular sulfur supply (+S, 500 μM), starvation (-S, two weeks at 0 μM) and recovery (-S → +S, 3 h at 500 μM) in roots of *parn* (red), *parn-ags1* (grey) and wildtype plants (black). Results were normalized to the expression values measured for wildtype plants under full nutrient supply. Bars represent standard errors (n = 3).

The *AGS1* gene encodes for a poly(A) polymerase, which acts as an antagonist of PARN. Since all of the known *parn* phenotypes are suppressed by loss-of-function mutations in *AGS1* [20,21], we expected the *parn-ags1* double mutants to reset their transcriptome to pre-starvation conditions just as readily as wildtype plants.

As suggested by publicly available microarray data [17,18], the transcript levels of *SULTR1;1, SULTR1;2, SHM7, SDI1* and *GGCT* did not differ considerably between wildtype plants and *parn* hypomorphic or *parn-ags1* double mutants under full nutrient supply. Upon starvation, a clear upregulation of the previously mentioned transcripts was observed in all genotypes. The strongest induction was measured for *GGCT* (33-fold for wildtype, 63-fold for *parn* and 32-fold for *parn-ags1*), whereas the transcript levels of *SULTR1;2* increased to a lesser extent (2-fold for wildtype, 2-fold for *parn* and 1.3-fold for *parn-ags1*). This is well in line with published transcript data from sulfur-starved wildtype plants [31,32] and supports the validity of the nutrient starvation conditions used. After sulfate resupply, the abundance of the five sulfur starvation marker transcripts decreased rapidly, not only in wildtype plants, but also in *parn* and *parn-ags1* mutants. With the exception of *SULTR1;1*, three hours of recovery were sufficient for the transcript levels to return to pre-starvation conditions. When this single time point was used as a basis for a rough estimation of transcript half-life, the measurements taken for wildtype plants indicated transcript half-lives of 151 minutes for *SULTR1;2*, 144 min for *SULTR1;1*, 58 min for *SHM7*, 40 min for *SDI1* and 29 min for *GGCT*.

Taken together, these results indicate that *parn* and *parn-ags1* mutants clear their transcriptomes of surplus sulfur-responsive transcripts just as readily as wildtype plants. This finding excludes a significant function of PARN and its antagonist AGS1 in the clearance of sulfur starvation-induced transcripts. Furthermore, it puts a note of caution on the identification of functional ARE sites in plants based on the currently available prediction tools (or data on mammalian ARE sites).

### *2.3. PARN Accumulates in Cytoplasmic Speckles*

The subcellular localization of enzymes provides the physiological context for their activity and determines their access to substrates and interaction partners [33]. Therefore, the identification of the subcellular localization of PARN and its antagonist—the poly(A) polymerase AGS1—is critical to understanding the biological role of the PARN-AGS1 mRNA degradation system.

In order to elucidate the subcellular localization of PARN and AGS1, we used stable transgenic lines expressing either PARN-GFP or AGS1-GFP under the control of their endogenous promoters [21]. These lines were germinated on agar-medium in the presence and absence of sulfur. Root sections from the tip to the elongation zone of ten-day-old seedlings were imaged for GFP signals after incubation, with dyes staining the mitochondria (MitoTracker, 100 nM for 15 min) and the nucleus (DAPI, 2 μg mL−<sup>1</sup> for 15 min). Under full nutrient supply, PARN-GFP localized exclusively to cytoplasmic speckles that were partly, but not entirely, overlapping with the mitochondrial signal. AGS1-GFP was found in cytosolic speckles, as well as in the nucleus, where it was evenly distributed (Figure 3). In order to demonstrate that the observed GFP signals were not bleed-through signals from the DAPI or the MitoTracker channel, wildtype plants were stained with both dyes (Figure S1). Since AGS1 is an antagonist of PARN, we hypothesized that PARN might also localize to the nucleus under certain conditions.

**Figure 3.** Under full nutrient supply, PARN-GFP (**a**) localizes to cytoplasmic speckles, whereas AGS1-GFP (**b**) is confined to the nucleus. Roots (tip and elongation zones) of ten-day-old PARN-GFP and AGS1-GFP seedlings grown under control conditions were left untreated (first row) or incubated with DAPI (second row) and MitoTracker Orange (third row). Each column represents a different channel (GFP, DAPI, MitoTracker). The last column shows a merge of all channels. Pictures are the result of maximum intensity z-projections of slices in a z-stack. Scale bar 10 μm.

Indeed, when the growth media were prepared without sulfur, in rare cases the subcellular localization of PARN-GFP shifted from cytoplasmic speckles to the nucleus (Figure S2a). AGS1-GFP, on the other hand, did not display any changes in localization upon nutrient starvation. To determine whether the starvation-induced relocalization of PARN to the nucleus was sulfur-specific or a general adaptation to nutrient starvation, the experiment was repeated with seedlings depleted of nitrogen (Figure S2b). Both nitrogen and sulfur are important macronutrients required for the synthesis of essential amino acids. As observed for sulfur depletion, nitrogen starvation induced a relocalization of PARN to the nucleus at a comparably low frequency. Similarly, reductive stress induced by 30 min of

10 mM dithiothreitol (DTT) caused PARN to shift its subcellular localization from cytosolic speckles to the nucleus (Figure S2c). Similar to nutrient starvation, the reductive stress treatment did not induce a comprehensive relocalization. However, the occasional relocalization of PARN-GFP under the applied stress conditions was never observed for the AGS1-GFP fusion under identical conditions (Figure S3).

### *2.4. PARN is Encoded for by Two Alternative Splice Variants Predicted to Localize to Di*ff*erent Cellular Compartments*

One possible explanation for the dual localization of PARN observed in our experiments is the existence of alternative PARN splice isoforms encoding for different protein variants confined to distinct cellular compartments. The Arabidopsis Information Resource (TAIR) provides sequences of four *At*PARN splice variants, A–D (Figure 4a). Since the splice variants A and D give rise to the same protein, the four splice variants encode for three distinct protein species. These species differ only in the length of their N-terminus (Figure 4b). Since the N-terminus is an important determinant of subcellular protein localization, the localization of the isoforms A–D was predicted by seven algorithms. While the splice variants A and B were predicted to localize to the nucleus or the cytoplasm (denoted as "N.A."), splice variant C was predicted to be confined to the mitochondria or the chloroplasts (Figure 4g).

To determine which of the four *PARN* transcripts were present in planta under full nutrient supply and sulfur starvation, the primers I–V detecting the splice variants A–D (Figure 4a) were used for a qRT-PCR analysis of cDNA extracted from starved and non-starved wildtype plants. By comparing the expected and observed fragments produced by the isoform-specific primers, the presence of the splice isoforms B and C could be verified in vivo. Isoforms A and D, however, were not detected. These results were further corroborated by the immunodetection of the splice variants B and C, but not A and D, in protein extracts from 10-day-old seedlings (Figure 4f). Remarkably, no difference in patterns between the seedlings grown under sulfur deficiency and full nutrient supply could be observed. Under both conditions, isoform C was expressed at an approximately 4-fold higher level than isoform B. No free GFP was detected, indicating that the nuclear GFP signal observed in PARN-GFP roots cannot be attributed to cleaved fluorophores, but is indeed an authentic GFP-PARN signal. Furthermore, the qRT-PCR analysis revealed that neither the total PARN transcript levels nor the ratio of isoform B to isoform C changed significantly when comparing full and limited nutrient supply (Figure 4e). The relative abundance of isoform B was calculated using the primer pair IV, whereas the primer pair V was used to determine the relative abundance of isoform C. Primer pair II was used to quantify the total PARN transcript level.

**Figure 4.** *At*PARN is encoded for by four splice variants. (**a**) Schematic structure of splice variants A–D. Their presence was verified with primer pairs I–V (indicated by arrows). While black boxes represent untranslated exons, blue boxes indicate translated exons. Introns are represented by black lines. (**b**) Proteins encoded for by transcripts A–D. The predicted nuclear localization signal (NLS) is marked with an asterisk. (**c**) Expected PCR products for primer pairs I–V in the presence of splice variants A–D. Most primer pairs may generate several amplicons of differing lengths, depending on which isoforms are actually present. Due to the extremely short annealing/extension step however, only the shortest amplicons (bold) are expected to be produced. (**d**) qRT-PCR products generated using primers I–V on cDNA from roots of starved (-S, 0 μM sulfur) and non-starved (+S, 500 μM sulfur) wildtype plants. As a negative control, the cDNA was substituted with H2O. (**e**) Relative abundance of splice variants B and C as well as total PARN transcripts under full nutrient supply and sulfur starvation in wildtype roots. (**f**) Immunodetection of the PARN-GFP isoforms B and C in protein extracts from sulfur-starved and non-starved seedlings with a polyclonal rabbit α-GFP antibody (# A-6455, Thermo Fisher Scientific). Amido black-stained protein served as the loading control. (**g**) Localization of isoforms A–D as predicted by seven independent algorithms (see 4.7). Since the cytosol is the default localization of a protein, cytosolic proteins will not yield any prediction by the aforementioned algorithms (denoted by "N.A.").

### **3. Discussion**

Plants as sessile organisms rely on transcriptional reprogramming to adapt to a constantly changing macronutrient supply. When exposed to sulfur limitation, they upregulate sulfate assimilation pathways, resulting in an accumulation of transcripts encoding for sulfur deficiency marker genes [1]. Upon cessation of the stress, however, those transcripts are subjected to rapid recovery downregulation [8,11]. In eukaryotes, mRNA decay is generally initiated by the deadenylation of transcripts [25]. As mutations in the poly(A) ribonuclease *At*PARN have been linked to altered abiotic stress responses in *Arabidopsis thaliana* [17–19], this manuscript investigated a few aspects of the role of PARN in the recovery from sulfur starvation.

### *3.1. The Degradation of Sulfur Starvation-Induced Genes during the Recovery from Starvation is Independent of AtPARN*

Although we identified putative PARN-recruiting AREs [25] in several sulfur starvation-induced transcripts, PARN is not required for their degradation upon recovery from starvation. When mutants of *parn* and its antagonist *ags1* were subjected to sulfur depletion followed by resupply, they degraded surplus sulfur-induced transcripts just as effectively as wildtype plants (Figure 2). The mRNA half-life estimations inferred from the observed transcript degradation rates of *GGCT*, *SDI1* and *SHM7* amounted to less than an hour. Since those calculations were based on only one time point, they can only provide a rough estimate of the upper limit of the mRNA half-life. In Arabidopsis, the average mRNA half-life is estimated to be in the order of several hours [10]. This indicates that even though PARN is not mediating the degradation of *GGCT*, *SDI1* and *SHM7*, other active mRNA degradation enzymes might act on those transcripts upon sulfur resupply. The sulfur-responsive transcripts might, for instance, be degraded by the cytoplasmic exoribonuclease XRN4. XRN4 has been shown to degrade the mRNA of heat shock factor HSFA2 and thereby represses heat stress responses after the return to normal temperature [34]. The fact that XRN4 targets specific transcripts involved in the response to abiotic and biotic stimuli [35] supports the notion that XRN4, rather than PARN, might be involved in the recovery from sulfur starvation in *Arabidopsis thaliana.*

### *3.2. The Presence of Two Alternative PARN Splice Variants Reconciles the Diverging Views on PARN Localization in the Literature*

We selected PARN as a candidate for rapid transcript degradation upon sulfur resupply because we identified putative PARN-recruiting AREs in mRNAs upregulated upon sulfur starvation. Transcripts harboring AREs are known to localize to the cytosolic sites of mRNA degradation, termed processing-bodies (p-bodies), where they are rapidly degraded [36].

According to translational fusions with GFP, PARN localizes to p-bodies when it is transiently expressed under the control of the 35S promoter in tobacco leaves [28]. This finding is discussed controversially in the literature, since it contradicts earlier PARN localization studies in onion epidermal peels, reporting a nuclear–cytoplasmic localization [16,29]. Both observations do however agree with the predominantly nuclear–cytosolic localization of PARN reported for metazoans. When *At*PARN-GFP expression is driven by the native PARN promoter, the fusion protein localizes to the mitochondria, indicating a unique function of PARN in higher plants [20,21].

Here we made use of stable transgenic PARN-GFP lines to show that under optimal nutrient supply, PARN localizes to cytoplasmic speckles. Unlike previously reported by Hirayama and co-workers [21], we did not observe full colocalization of those speckles with the mitochondria. Our findings suggest that PARN might localize to the mitochondria, but a considerable portion of the observed PARN-GFP signal is localized to p-bodies [28]. Since p-bodies are involved in the degradation and translational arrest of transcripts during development and the adaptation to stress, this subcellular localization agrees with the biological function of PARN observed in mammals.

Furthermore, we found that mineral nutrient deficiency and reductive stress in rare cases induces a dynamic delocalization of PARN from cytoplasmic speckles to the nucleus. The fact that this delocalization was observed under several stress conditions points to a general cellular mechanism. Although the function of PARN in the nucleus remains unknown, the stress-induced delocalization system we describe here opens new avenues to study the function of nuclear-localized PARN.

A potential mechanism for the stress-induced delocalization of the PARN protein is the existence of different PARN splice variants as evidenced by The Arabidopsis Information Resource (TAIR). These variants encode for proteins that differ only in the length of their N-terminus. Whereas the full-length *At*PARN splice variant carries an N-terminal extension that distinguishes *At*PARN from putative animal homologs [20], the shorter *At*PARN variants lack this non-conserved N-terminus. When subjected to intracellular targeting algorithms, the different *At*PARN splice variants are bioinformatically predicted to localize to distinct subcellular compartments. It is worth noting that three of the seven applied prediction algorithms (iPSORT, TargetP and Predotar) focus on N-terminal sorting signals to determine the localization of proteins [37–39]. Thus, their predictions are biased towards mitochondrial and chloroplastic localizations. While the full-length protein is predicted to localize to the mitochondria, the shorter variants are thought to localize to the nucleus and the cytoplasm. We detected two out of the four *At*PARN splice variants in roots of wildtype Arabidopsis plants. These splice variants are predicted to localize to the nucleus or the cytoplasm and the mitochondria.

Profiling of *PARN* transcripts from roots revealed that both splice forms were present at similar levels under optimal or sulfur-depleted conditions. Hence, changes in the transcription or processing of both variants cannot directly explain the sulfur limitation-induced delocalization of PARN in roots. However, both splice variants were present in roots under full nutrient supply as well as starvation conditions, which potentially enables stress-induced differential loading of the transcripts to ribosomes. Indeed, in yeast and mammalian somatic cells, thousands of untranslated mRNAs were shown to be targeted to p-bodies, where they are translationally repressed, suggesting that p-bodies provide a reservoir for quick adaptation of gene expression [40]. Similarly, plant p-bodies might act as reservoirs for the two *PARN* transcript variants, enabling plants to react to stresses without the delay caused by a transcriptional regulation of *PARN*.

Immunodetection of *At*PARN under standard growth conditions and sulfur depletion, however, revealed no shift in the ratio between isoform B and C on the protein level. Most likely, the expression of isoform B is not sufficient to induce nuclear localization but requires stress-induced post-translational modifications of PARN or the binding of PARN to interaction partners. Both mechanisms have previously been described for other proteins. The Arabidopsis leucine zipper transcription factor VIP1, for instance, is dephosphorylated upon mechanical and hypo-osmotic stress and subsequently changes its localization from the cytosol to the nucleus [41]. In mammalian cells, RNA-binding proteins move from the cytoplasm to the nucleus in response to accelerated mRNA decay associated with cellular stress. In some cases, this delocalization is mediated via direct interaction of those proteins with the nuclear transport machinery. In other cases, interactions with proteins containing NLS are responsible for the import into the nucleus. On the other hand, PARN might be sequestered in the cytosol via interaction with cytosolic proteins. In accordance with this hypothesis, the BioAnalyticResource Tool Arabidopsis Interaction Viewer predicts PARN to interact with two cytosolic proteins (AT5G47010 and AT2G39260) required for nonsense-mediated mRNA decay. The mechanism of PARN delocalization will be the subject of further studies.

### **4. Materials and Methods**

### *4.1. Plant Material and Growth Conditions*

All work was performed with *Arabidopsis thaliana* ecotype Columbia-0 (Col-0). The transgenic *parn* knockdown, *parn-ags1* double mutant, PARN-GFP and AGS1-GFP lines are characterized in [19,21]. All experiments except the subcellular localization study and the sulfur resupply assay (described below) were conducted with plants grown under short-day conditions (8.5 h light, 100 μE light photon

flux density, 24 ◦C by day, 18 ◦C by night and 50% humidity) on a medium containing one half soil and one half substrate 2 (Klasmann-Deilmann, Germany).

### *4.2. Sulfur Resupply Assay*

In order to determine the role of *At*PARN in the recovery from sulfur starvation, *parn*, *parn-ags1* and wildtype seeds were surface-sterilized with 70% (v/v) ethanol for 5 min followed by 6% sodium hypochlorite for 3 min and a second wash with 70% (v/v) ethanol for 5 min. Afterwards, the seeds were washed trice with ddH2O. Individual seeds were placed in microcentrifuge tubes containing 1 <sup>2</sup> Hoagland medium (0.5 mM KH2PO4, 0.05 μM (NH4)6Mo7O24 · 4 H2O, 0.5 mM MgSO4/MgCl2, 0.15 μM CuSO4 · 5 H2O, 2.5 mM Ca(NO3)2 · 4 H2O, 1.9 μM ZnSO4 · 7 H2O, 2.5 mM KNO3, 10 μM NaCl, 2.25 μM MnCl2 · 4 H2O, 25 μM H3BO3, 40 μM Fe-EDTA; pH 5.8) supplemented with 0.6% (w/v) agar. Subsequently, the tubes were inserted in standard 1 mL pipette tip racks. Plants were stratified at 4 ◦C for three days before being germinated in a short-day growth cabinet. After two weeks, individual plants were transferred to 6 liter boxes containing <sup>1</sup> <sup>2</sup> Hoagland medium. After an additional two weeks of growth on full medium, a subset of the plants was starved for sulfur by replacing MgSO4 in the Hoagland medium with MgCl2. The control group continued to receive full medium. Starvation lasted for two weeks, with media being exchanged on a weekly basis. Subsequently, root and shoot material were collected and snap-frozen in liquid nitrogen.

### *4.3. Genotyping by PCR*

In order to identify the transgenic plants, gDNA was extracted from 50–100 mg Arabidopsis leaf material. The fresh tissue of four-week-old plants was ground with a plastic pestle for 10–15 sec. Subsequently, 400 μL Edwards buffer (200 mM Tris/HCl, 25 mM EDTA, 250 mM NaCl, 0.5% SDS) were added and the mixture was vortexed for 5 sec. After centrifugation at 13.000 rpm for 5 min at room temperature, 300 μL of supernatant were transferred to a fresh microfuge tube. 300 μL 100% isopropanol were added and the mixture was left to incubate for two minutes at room temperature. After centrifugation at 13,000 rpm for 10 min at room temperature, the supernatant was discarded and the pellet was washed with 700 μL 70% ethanol. After a final centrifugation step at 13,000 rpm for 10 min, the ethanol was discarded and the DNA pellet was resuspended in 40 μL ddH2O. Subsequently, 20 ng of the harvested gDNA were used for PCR reactions performed with the GoTaq® Green Master Mix (Promega) and specific primers (see Appendix A Table A1).

### *4.4. Quantifying Gene Expression by qRT-PCR*

To analyze the transcript levels of sulfur starvation-induced genes, total RNA was extracted from frozen leaf and root material using the peqGOLD total RNA kit (PeqLab). Subsequently, total RNA was transcribed into complementary DNA (cDNA) with the RevertAid H Minus First Strand cDNA Synthesis Kit using oligo(dT) primers (Thermo Fisher Scientific). All reactions were conducted according to the supplier's protocol. The cDNA was analyzed by qRT-PCR with the SqPCRBIO SyGreen Mix Lo-ROX (Nippon Genetics Europe GmbH) and *TIP41* (AT4G34270, [42]) and *PP2A* (AT1G69960, [43]) as reference genes. The corresponding primer sequences are listed in Table A3 of the Appendix A. Data was analyzed via the Rotor-Gene Q Series Software.

In order to quantify the amount of transcripts that encode for alternatively spliced forms of *At*PARN, primers that discriminated between the mRNA models A–D were designed and used for qRT-PCR (see Table A2 of the Appendix A for sequences). The four models encode for the cDNA clones AK227465 and AB223028 (A), AB223029 (B), AB19466 (C) and AB223027 (D). To ensure that each primer pair produced only the shortest possible fragment, the annealing time was reduced to 20 sec. As a quality control measure, a melting curve (ramp from 63 ◦C–95 ◦C rising by 1 ◦C per step) was recorded. Additionally, the qRT-PCR products were visualized on agarose gels (0.8% agarose in 40 mM Tris, 20 mM acetic acid, 1 mM EDTA, pH 8.0).

The shares of the individual isoforms A–D of the total transcript amount of *At*PARN were calculated based on the ΔΔCT method [44].

### *4.5. Immunodetection of PARN-GFP*

Total proteins were extracted from 10-day-old PARN-GFP and wildtype seedlings sown on <sup>1</sup> 2 Hoagland medium supplemented with 0.8% agarose and either 0 μM (-S) or 500 μM (+S) sulfate. After extraction in 80 mM Tris-HCl (pH 7.5), 300 mM NaCl, 1 mM EDTA, 1 mM PMSF, 10 mM DTT, 1% TritonX and 1 tablet EDTA-free protease Inhibitor cocktail per 50 mL (Roche), the samples were subjected to discontinuous SDS–PAGE in Mini-ProteanTM II cells (BioRad), followed by immunoblotting with a polyclonal rabbit α-GFP antibody (# A-6455, Thermo Fisher Scientific) diluted 1:5000 in TBS-T (50 mM Tris pH 7.6, 150 mM NaCl, 0.05% Tween-20). After blocking for 1 h with 5% BSA in TBS-T, the blot was washed trice with TBS-T before the addition of the primary antibody, which was left to incubate overnight at 4 ◦C. Subsequently, the blot was washed trice with TBS-T and the secondary horseradish peroxidase-linked anti-rabbit antibody (#AS10 852, Agrisera) diluted 25,000-fold in TBS-T was left to incubate for 1 h. Membranes were developed using SuperSignal West Dura Extended Duration Substrate (Thermo Fisher Scientific) according to the manufacturer's protocol. The resulting signals were recorded using the ImageQuant LAS 4000 (GE Healthcare).

### *4.6. Subcellular Localization*

To assess the subcellular localization of *At*PARN and its antagonist AGS1, *At*PARN-GFP and AGS1-GFP seeds were sterilized as described previously and sown on <sup>1</sup> <sup>2</sup> Hoagland medium supplemented with 0.8% agarose. The plants were stratified at 4 ◦C in the dark for three days before they were transferred to long-day conditions (16 h light, 100 μE light photon flux density, 24 ◦C by day, 18 ◦C by night and 50% humidity). In order to visualize the mitochondria, 10-day-old seedlings were incubated with 100 nM MitoTracker™ Orange CMTMRos (Thermo Fisher Scientific) in <sup>1</sup> <sup>2</sup> Hoagland medium for 15 min as described in [21]. For nuclear staining, samples were incubated for 15 min with 2 μg mL−<sup>1</sup> DAPI (Sigma-Aldrich) in <sup>1</sup> <sup>2</sup> Hoagland medium supplemented with 1:20,000 Triton-X. Samples grown on -S plates were incubated in staining solutions prepared with -S <sup>1</sup> <sup>2</sup> Hoagland medium. For the DTT treatment, seedlings were floated for 30 min in <sup>1</sup> <sup>2</sup> Hoagland medium supplemented with 10 mM DTT before staining with MitoTracker or DAPI. Subsequently, the roots were separated from the seedlings and imaged with a Nikon automated Ti inverted microscope equipped with a Yokagawa CSU-X1 confocal scanning unit, a Hamamatsu C9100-02 EMCCD camera and a Nikon Plan Apo VC 100x NA 1.4 oil immersion objective (Nikon). Images were taken as z-stacks with an approximate thickness of 1 μm. Images were taken in three different channels (DAPI: 405 nm/445 nm; GFP 488 nm/527 nm; MitoTracker 561 nm/615 nm). Additionally, a brightfield image was recorded. The resulting z-stacks were processed with the open-source image analysis software Fiji [45]. For each channel, a maximum intensity z-projection image was calculated. Subsequently, the background fluorescence intensity was measured and subtracted for each channel.

### *4.7. Identification and Functional Annotation of Genes with mRNA Destabilizing Motifs*

Sequence data for all known 3- UTRs of cytosolic mRNAs was downloaded from The Arabidopsis Information Resource (TAIR) (TAIR10 blastsets, TAIR10\_3\_utr\_20101028, as of 10.11.2010). Subsequently, pattern match algorithms were devised to search the sequence strings for the occurrence of the core sequence "AUUUA", characteristic for AU-rich elements.

### *4.8. Prediction of Subcellular Protein Localization*

The subcellular localization of *At*PARN was predicted based on its amino acid sequence. For that purpose, several bioinformatical tools, including Predotar [37], iPSORT [38], Target [39], SherLock2 [46], BaCelLo [47], WoLF PSORT [48] and YLoc [49] were applied.

The presence of nuclear localization signals was predicted with the public NLS db server (to be found at www.rostlab.org/services/nlsdb/, as of 13.04.2018).

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2223-7747/8/10/380/s1, Figure S1: Wildtype seedlings stained with DAPI and MitoTracker display no signal in the GFP channel, Figure S2: AGS1-GFP does not change its subcellular localization upon nutrient starvation, Figure S3: AGS1-GFP does not change its subcellular localization upon nutrient starvation.

**Author Contributions:** Conceptualization, R.H., V.V.U. and L.A.; methodology, L.A.; formal analysis, L.A.; investigation, L.A.; data curation, L.A.; writing—original draft preparation, L.A.; writing—review and editing, M.W. and L.A.; visualization, L.A.; supervision, R.H., M.W. and V.V.U.; project administration, M.W. and R.H.; funding acquisition, M.W. and R.H.

**Funding:** This research benefitted from funding grants held by M.W. (WI3560/1-1, -/2-1) and R.H. (HE1848/115-1,).

**Acknowledgments:** The authors want to thank Takashi Hirayama (Okayama University, Japan) for the kind gift of *parn* hypomorphic and *parn-ags1* mutants, as well as the AGH2-GFP and AGS1-GFP lines.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **Appendix A**


**Table A1.** Primers used to genotype transgenic plant lines.

**Table A2.** Primers used to identify *At*PARN splice variants.



**Table A3.** Primers used to assess abundance of genuine sulfur-responsive transcripts.

### **References**


© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

### *Article* **Glucosinolate Distribution in the Aerial Parts of** *sel1-10***, a Disruption Mutant of the Sulfate Transporter SULTR1;2, in Mature** *Arabidopsis thaliana* **Plants**

### **Tomomi Morikawa-Ichinose 1, Sun-Ju Kim 2, Alaa Allahham 1, Ryota Kawaguchi <sup>1</sup> and Akiko Maruyama-Nakashita 1,\***


Received: 26 February 2019; Accepted: 4 April 2019; Published: 10 April 2019

**Abstract:** Plants take up sulfur (S), an essential element for all organisms, as sulfate, which is mainly attributed to the function of SULTR1;2 in *Arabidopsis*. A disruption mutant of *SULTR1;2, sel1-10,* has been characterized with phenotypes similar to plants grown under sulfur deficiency (−S). Although the effects of −S on S metabolism were well investigated in seedlings, no studies have been performed on mature *Arabidopsis* plants. To study further the effects of −S on S metabolism, we analyzed the accumulation and distribution of S-containing compounds in different parts of mature *sel1-10* and of the wild-type (WT) plants grown under long-day conditions. While the levels of sulfate, cysteine, and glutathione were almost similar between *sel1-10* and WT, levels of glucosinolates (GSLs) differed between them depending on the parts of the plant. GSLs levels in the leaves and stems were generally lower in *sel1-10* than those in WT. However, *sel1-10* seeds maintained similar levels of aliphatic GSLs to those in WT plants. GSL accumulation in reproductive tissues is likely to be prioritized even when sulfate supply is limited in *sel1-10* for its role in S storage and plant defense.

**Keywords:** mature *Arabidopsis thaliana* plants; sulfate transporter; SULTR1;2; *sel1-10* mutant; glucosinolates

### **1. Introduction**

Sulfur (S) is an essential macronutrient for all organisms. Plants take up inorganic sulfate as the major S source and assimilate it into a variety of S-containing organic compounds [1,2]. As animals are unable to assimilate sulfate, the role of plants in the global S cycle on the earth is extremely important [2]. In addition, many of the S-containing compounds biosynthesized in plants are beneficial to health, such as methionine (an essential amino acid for animals), glutathione (a redox controller), and various secondary compounds with specific functions [2]. Glucosinolates (GSLs) are the major S-containing secondary compounds biosynthesized in *Brassicaceae*, that act as defense compounds against insects and pathogens [3–5]. Depending on their amino acid precursors, most GSLs accumulated in *Arabidopsis* are classified into aliphatic and indolic GSLs (iGSLs) synthesized from methionine and tryptophan, respectively [3–5]. Among them, some aliphatic GSLs (mGSLs) are known to be beneficial for humans as cancer-preventive chemicals [6,7]. Thus, understanding GSL accumulation in plant tissues would contribute to improved food quality in Brassica crops.

The composition and content of GSLs are different among plant parts in *Arabidopsis* [8–12]. Most GSLs accumulated in developing rosette leaves are mGSLs, and mainly consist of 4-methylsulfinylbutyl GSL (4MSOB, 34 to 60%), 3-methylsulfinylpropyl GSL (3MSOP, 4 to 9%), 4-methylthiobutyl GSL (4MTB, 1 to 23%), and 8-methylsulfinyloctyl GSL (8MSOO, 2 to 6%). The remaining GSLs are iGSLs, and mostly comprise indol-3-ylmethyl GSL (I3M, 11 to 23%) [8,9,13]. Cauline leaves and stems have a similar concentration and composition to that of rosette leaves [9]. GSL content in the seeds is 3.5 to 8.5-fold than that in the leaves, with the higher GSL variations characterized by a higher amount of 4MTB (37 to 41%); the long-chain mGSLs, such as 8MSOO (9.9 to 10%), 8-methylthiooctyl GSL (8MTO, 6.9 to 7.4%), 7-methylthioheptyl GSL (7MTH, 4.7 to 4.8%), and 7-methylsulfinylheptyl GSL (7MSOH, 1.8 to 2.4%); as well as with a relatively low amount of I3M (2.3 to 2.9%) [8,9]. mGSLs are structurally divided into methylsulfinylalkyl (MSOX) GSLs (3MSOP, 4MSOB, 7MSOH, and 8MSOO) and methylthioalkyl (MTX) GSLs (4MTB, 7MTH, and 8MTO) [3–5,7]. Seeds accumulated more MTX GSLs than MSOX GSLs compared to the other tissues [8,9]. The GSL concentration in the siliques is lower than that in the seeds, and the composition is intermediate of that in the rosette leaves and the seeds [8,9]. This plant part-specific variation in GSL concentration and composition suggests that GSL accumulation is controlled by different mechanisms in each part [8–12].

GSL content in plants is also influenced by environmental factors [5,14]. For example, it is stimulated by glucose and jasmonic acid [15,16], and is increased upon pathogen infection [17,18] and insect bite [19]. Among the environmental factors, nutritional conditions, particularly S status, greatly influence GSL accumulation in plants [13,20–22]. GSL synthesis and accumulation are stimulated under S sufficiency (+S) but suppressed under S deficiency (−S), which is regulated by specific transcriptional networks induced by −S in *Arabidopsis* [5,13,20,22–24]. However, these experiments were mostly undertaken on seedlings and the effects of –S on GSL accumulation in mature plants have not been reported.

Previous studies have shown a close correlation between the effects of −S and the disruption of SULTR1;2, a major sulfate transporter that facilitates sulfate uptake from roots [25–28]. In this study, we examined the accumulation of S-containing compounds in aerial tissues of mature SULTR1;2 mutants, known as *sel1-10*, and wild-type (WT) plants to clarify the distribution of sulfate as well as cysteine and glutathione in relation to the distribution of GSL in the mature plants.

### **2. Results**

### *2.1. Growth Phenotypes of WT and sel1-10 Plants*

To investigate the metabolic changes occurring in mature *sel1-10* plants, we initially observed the growth phenotypes of *sel1-10* plants (Figure 1). WT and *sel1-10* plants were grown for six weeks in vermiculite. Although visible differences in shoot phenotype were not observed between WT and *sel1-10* plants (Figure 1a,b), a significant decrease was observed in the primary stem diameters of *sel1-10* plants compared to those of the WT, while the plant heights were similar between WT and *sel1-10* plants (Figure 1c). Correlated with the decrease in primary stem diameter in *sel1-10*, dry weight of primary stems (PS) was decreased in *sel1-10* to 70% of that in WT plants (Figure 1d). Dry weights of rosette leaves (RL), cauline leaves (CL), lateral stems (LS), and siliques (Si) were not significantly lower but tended to be lower in *sel1-10* plants relative to those in WT plants (Figure 1d).

**Figure 1.** Growth phenotypes of wild-type (WT) and *sel1-10* plants. (**a**) WT and *sel1-10* plants grown for six weeks on vermiculite. (**b**) Siliques (upper panels) and primary stems (lower panels) of WT and *sel1-10* plants. Scale bar = 1 cm. (**c**) Plant heights and diameters of primary stems of WT and *sel1-10* plants. (**d**) Dry weight of rosette leaves (RL), cauline leaves (CL), primary stems (PS), lateral stems (LS), and siliques (Si) in WT and *sel1-10* plants. White and green bars represent WT and *sel1-10*, respectively, in (**c**) and (**d**). Data are shown as the averages with error bars denoting SEM (n = 5). Asterisks indicate significant differences (Student's *t*-test; \*\* *p* < 0.05) between WT and *sel1-10*.

### *2.2. Concentrations of Sulfate and Selected Sulfur-Containing Metabolites in Different Parts of WT and sel1-10 Plants*

We harvested RL, CL, PS, LS, and Si separately and analyzed sulfate, cysteine, glutathione (GSH), and GSL in different parts of the *sel1-10* and WT plants (Figures 2–4).

Sulfate content in the RL of *sel1-10* plants was 26% higher than that in the WT plants. Both WT and *sel1-10* plants accumulated a similar level of sulfate in CL, PS, and LS. In Si, the sulfate content of *sel1-10* plants was 61% of that in the WT plants. These results indicated that the distribution of sulfate was modulated in *sel1-10* plants.

To examine the effects of modulated sulfate distribution in *sel1-10*, cysteine and GSH contents in WT and *sel1-10* plants were analyzed (Figure 3). Cysteine content was not significantly different between WT and *sel1-10* plants in all examined parts. The GSH content in Si of *sel1-10* plants was 29% lower than that in WT plants, suggesting that the dysfunction of SULTR1;2 affects GSH accumulation in reproductive tissues as observed in the seedlings [28]. GSH content in other parts of *sel1-10* plants was similar to that in the WT plants.

**Figure 2.** Sulfate concentrations in different parts of WT and *sel1-10* plants. Sulfate content in each part was determined by ion chromatography. WT and *sel1-10* seedlings were grown for six weeks in vermiculite, and each part was harvested. Rosette leaves (RL), cauline leaves (CL), primary stems (PS), lateral stems (LS), and siliques (Si). White and green bars represent the sulfate content in WT and *sel1-10*, respectively. Data are shown as averages with error bars denoting SEM (n = 3). Asterisks indicate significant differences (Student's *t*-test; \* 0.05 < *p* < 0.1, \*\* *p* < 0.05) between WT and *sel1-10* plants.

**Figure 3.** Cysteine and glutathione (GSH) concentrations in different parts of WT and *sel1-10* plants. The cysteine and GSH contents of different parts were measured using HPLC-fluorescence detection. WT and *sel1-10* seedlings were grown for 6 weeks in vermiculite, after which each part was harvested. Rosette leaves (RL), cauline leaves (CL), primary stems (PS), lateral stems (LS), and siliques (Si). White and green bars represent cysteine and GSH levels in WT and *sel1-10* plants, respectively. Data are shown as the averages with error bars denoting SEM (n = 3). Asterisks indicate significant differences (Student's *t*-test; \* 0.05 < *p* < 0.1, \*\* *p* < 0.05) between WT and *sel1-10* plants.

The following seven major GSLs were analyzed in both plants (Figure 4). These included six mGSLs: 3-methylsulfinylpropyl GSL (3MSOP), 4-methylsulfinylbutyl GSL (4MSOB), 8-methylsulfinyloctyl GSL (8MSOO), 4-methylthiobutyl GSL (4MTB), 7-methylthioheptyl GSL (7MTH), and 8-methylthiooctyl GSL (8MTO), and one iGSL, indol-3-ylmethyl GSL (I3M).

GSL levels were generally lower in RL, CL, PS, and LS of *sel1-10* relative to the same parts of WT plants (Figure 4). However, in Si, GSL levels did not significantly vary between *sel1-10* and WT plants, and some GSL levels were even higher in *sel1-10* plants relative to the WT plants, that is, the levels of MSOX GSLs and I3M were similar between *sel1-10* and WT plants, but the levels of MTX GSLs were higher in *sel1-10* plants relative to the WT plants (Figure 4).

Because GSL levels in Si were not affected in *sel1-10* plants except for 4MTB and 7MTH, GSL levels in mature dried seeds were analyzed to determine the effects of reduced sulfate uptake (Figure 5). Seeds contained much higher levels of MTX GSLs and 8MSOO and lower levels of I3M compared to other vegetative tissues in both plant lines, which is consistent with previous studies [8,9]. In seeds, GSL levels did not significantly vary between *sel1-10* and WT plants.

**Figure 4.** Glucosinolates (GSL) accumulation in different parts of WT and *sel1-10* plants. GSL levels in different parts were determined by LC-MS. The relative amount was calculated as the ratio of peak height of each GSL to that of the internal standard (L(+)-10-camphor sulfonic acid) and then divided by the dry weight of the sample. WT and *sel1-10* seedlings were grown for 6 weeks in vermiculite, after which, each part was harvested. (**a**) 3-methylsulfinylpropyl GSL (3MSOP), (**b**) 4-methylsulfinylbutyl GSL (4MSOB), (**c**) 8-methylsulfinyloctyl GSL (8MSOO), (**d**) 4-methylthiobutyl GSL (4MTB), (**e**) 7-methylthioheptyl GSL (7MTH), (**f**) 8-methylthiooctyl GSL (8MTO), (**g**) indol-3-ylmethyl GSL (I3M). Rosette leaves (RL), cauline leaves (CL), primary stems (PS), lateral stems (LS), and siliques (Si). White and green bars represent the relative GSL content in WT and *sel1-10* plants, respectively. Data are shown as averages with error bars denoting SEM (n = 3). Asterisks indicate significant differences (Student's *t*-test; \* 0.05 < *p* < 0.1, \*\* *p* < 0.05) between WT and *sel1-10* plants. n.d., not detected. The chemical structures of the GSLs were obtained from KEGG Databases in DBGET (https://www.genome.jp/dbget/).

**Figure 5.** GSL accumulation in mature seeds of WT and *sel1-10* plants. GSL levels in seeds were determined by LC-MS. The relative amount was calculated as the ratio of peak height of each GSL to that of the internal standard (L(+)-10-camphor sulfonic acid) and then divided by the dry weight of the sample. (**a**) 3-methylsulfinylpropyl GSL (3MSOP), (**b**) 4-methylsulfinylbutyl GSL (4MSOB), (**c**) 8-methylsulfinyloctyl GSL (8MSOO), (**d**) 4-methylthiobutyl GSL (4MTB), (**e**) 7-methylthioheptyl GSL (7MTH), (**f**) 8-methylthiooctyl GSL (8MTO), (**g**) indol-3-ylmethyl GSL (I3M). White and green bars represent the relative GSL content in WT and *sel1-10* seeds, respectively. Data are shown as averages with error bars denoting SEM (n = 3). Statistical analysis was performed with Student's *t*-test between WT and *sel1-10* plants, but any significant differences were not detected.

### **3. Discussion**

Growth phenotypes of mature *sel1-10* plants have not been well studied as regards their aerial part. The sulfate uptake rate in *sel1-10* plants was almost half of that in WT plants under both +S and –S conditions at the seedling stage [27,29]. In addition, the biomass and the levels of sulfate and GSH in *sel1-10* seedlings were significantly lowered relative to those in the WT plants under both +S and –S conditions [27–29]. Similar growth retardation in mature *sel1-10* plants observed in Figure 1 is assumed to be due to the reduction in sulfate uptake in *sel1-10* plants.

It is known that GSL accumulation is differentially regulated in plant parts and S status [8,9,13,21,22]. In our analysis, the levels of MSOX GSLs and I3M in the leaves and stems of *sel1-10* plants were significantly lower than those in the WT plants (Figure 4), in agreement with the –S-induced-like phenotypes observed in *sel1-10* seedlings [27,28]. In contrast, the GSL levels in Si and Se of *sel1-10* plants were similar or higher than those in WT plants (Figures 4 and 5). Considering the previous theory that GSLs accumulated in the seeds provide an S source for seedling growth [8–10,21], GSL accumulation should be prioritized in reproductive tissues even when the S supply is limited in *sel1-10* plants. Plants should have adapted to fluctuations in S availability by using GSLs as S storage substances in reproductive tissues. GSLs can be considered as a beneficial S storage compounds because of the relatively high molecular weight, that enable them to reduce osmotic pressure in the seeds. Additionally, GSLs can be a source of carbon and nitrogen, especially in the case of long-chain mGSLs highly accumulated in the seeds, and can also act as the defense compounds to protect the seeds from diseases or predators [11,21].

Unexpectedly, the levels of MTX GSLs were higher in Si of *sel1-10* plants compared to those in the WT plants, while MSOX GSL and iGSL levels in Si were similar between *sel1-10* and WT plants (Figure 4). Taking into account that GSL levels in Si were the sum of the levels in silique tissues, including the developing seeds, and all samples were collected on the same date, the increase of MTX GSLs could be because of the acceleration of seed maturation in *sel1-10* plants. In general, nutrient stress accelerates bud appearance and subsequent development of the siliques and seeds in *Arabidopsis* [30,31]. Considering that MTX GSLs in the seeds are continuously increased during the seed maturation period [8,9], the timing of flowering and seed development may occur earlier in *sel1-10* than in the WT plants. Lower levels of sulfate and GSH in Si of *sel1-10* plants relative to those in the WT plants also support this assumption (Figures 2 and 3).

Several maternal tissues have been suggested as source tissues for seed GSLs, including the leaves and siliques [10,11]. Although the GSL transport machinery in whole plants is not fully understood [10–12,32], GSL transporters, GTR1 and GTR2, that belong to the NRT/PTR family have been characterized for their roles [32,33]. In the double disruption lines of GTR1 and GTR2, most GSLs were not found in the seeds, whereas, mGSLs were highly accumulated in rosette leaves and siliques [32,33]. This suggested that seed GSLs are mostly transported from the source tissues. Decreased GSL levels in vegetative tissues and the maintenance of GSL levels in the seeds suggested that GSL transport to the seeds was not restricted or was even accelerated in *sel1-10* plants.

In conclusion, we found that GSL levels of the MSOX group were decreased in the leaves and stems, whilst all GSL were found to be maintained in the seeds in *sel1-10* plants. This shows that accumulation of mGSL characterizes the reproductive tissues, thus indicating that mGSL are destinated to store in the seeds in order to support the initial growth of the next generation.

### **4. Materials and Methods**

### *4.1. Plant Materials and Growth Conditions*

*Arabidopsis thaliana* were cultured in a growth chamber controlled at 23 ± 2 ◦C under constant illumination (40 μmol m−<sup>2</sup> s−1). The *sel1-10* mutant, carrying a T-DNA insertion in the ninth exon of SULTR1;2 (At1g78000) [28], and the background Wassilewskija (Ws-0) wild-type plants (WT) were used as plant materials. Seeds of WT and *sel1-10* were sown on vermiculite as growth substrate supplemented with MGRL mineral nutrient media in 5 × 5 × 5 cm plastic pots [34,35]. After germination, the number of plants was adjusted to three plants per pot. Plants were grown for 6 weeks and the different parts of the plants, rosette leaves (RL), cauline leaves (CL), primary stems (PS), lateral stems (LS), and siliques (Si) were harvested separately from each pot and weighed for the fresh weights. Mature dried seeds collected from the former generation were used for the analysis. Right after harvest, plant tissues were frozen in liquid nitrogen, freeze-dried, ground into a fine powder using a Tissue Lyser (Retsch, Germany), and used for each metabolite analysis. Three independent samples for each part were used for metabolite analysis.

### *4.2. Measurement of Glucosinolates*

Three milligrams of the plant powder was extracted with 300 μL of ice-cold 80% methanol containing 2 μM L(+)-10-camphor sulfonic acid (10CS, internal standard, Tokyo Kasei, Japan) using a Tissue Lyser. After homogenization, cell debris was separated by centrifugation (15,000 rpm, 10 min, 4 ◦C), and the supernatants were evaporated with a centrifugal evaporator (CVE-3110, EYELA, Japan) connected to a high vacuum pump (DAH-60, ULVAC, Japan) and a cold trap (UNI TRAP UT-1000, EYELA). Dried supernatants were dissolved into water, filtered with Millex-GV filter units (Millipore, USA), and analyzed by a high-performance liquid chromatograph connected to a triple quadrupole (LC-QqQ)-MS (LCMS8040, Shimadzu, Kyoto, Japan) using L-column 2 ODS (pore size 3 μm, length 2.1 × 150 mm, CERI, Japan). The mobile phase consisted of solvent A (0.1% formic acid, Wako Pure Chemicals, Osaka, Japan) and solvent B (0.1% formic acid in acetonitrile, Wako Pure Chemicals, Osaka, Japan). The gradient elution program was as follows with a flow rate of 0.3 mL/min, 0–0.1 min, 1% B; 0.1–15.5 min, 99.5% B; 15.5–17 min, 99.5% B; 17–17.1 min, 1% B; and 17.1–20 min, 1% B as described previously [36]. For the MS, electrospray ionization mass spectrometry technique in negative ionization mode was used. The ionization parameters were as follows: the nebulizer gas flow was 1.5 L/min, the CDL temperature was 250 ◦C, heat block temperature was 400 ◦C. All GSLs were detected with optimized selective reaction monitoring transitions in negative ionization mode as follows (precursor ion [*m/z*]/product ion [*m/z*] scores are shown): 3MSOP GSL: 422.02/358.02, 422.02/96.9, 422.02/95.9; 4MSOB GSL: 436.05/96.9, 436.05/96.0, 436.05/177.9; 8MSOO GSL: 492.1/428.1, 492.1/96.9, 492.1/95.9; 4MTB GSL: 420.04/96.9, 420.04/95.9, 420.04/74.9; 7MTH GSL: 462.09/96.9, 462.09/95.9, 462.09/74.9; 8MTO GSL: 476.11/96.9, 476.11/95.9, 476.11/74.9; I3M GSL: 447.05/96.9, 447.05/95.9, 447.05/74.9. MRM transitions were determined by using standard compounds (Cfm Oskar Tropitzsch GmbH, Marktredwitz, Germany) or a database (MassBank, http://www.massbank.jp). The relative quantities of GSLs were calculated as the ratio of peak height to the height of 10CS.

### *4.3. Measurement of Sulfate, Cysteine and Glutathione*

One mg of the plant powder was extracted with 200 μL of 10 mM HCl. The cell debris was removed by centrifugation, and the supernatant was used for the analysis. The extracts were diluted 100 fold with extra pure water and analyzed by ion chromatography as described previously [29], using an eluent containing 1.9 mM NaHCO3 and 3.2 mM Na2CO3.

Cysteine and GSH contents were determined by monobromobimane (Invitrogen) labeling of thiol bases after reduction of the extracts with dithiothreitol (Nacalai Tesque) as described [13,28,29]. The labeled products were then separated by HPLC (JASCO, Tokyo, Japan) using the TSKgel ODS-120T column (150 × 4.6 mm, TOSOH) and detected with a fluorescence detector FP-920 (JASCO), monitoring for fluorescence of thiol-bimane adducts at 478 nm under excitation at 390 nm. GSH and Cys standards were purchased from Nacalai Tesque (Kyoto, Japan).

### *4.4. Statistical Analysis*

The data were statistically analyzed using Student's *t*-test with Microsoft Excel. Significant differences between WT and *sel1-10* in biological replicates are shown in each Figure.

**Author Contributions:** A.M.-N. designed research. T.M.-I., A.A., R.K. and S.-J.K. performed experiments and analyzed data. T.M.-I. and A.M.-N. wrote the manuscript.

**Funding:** This work was supported by Grant-in-Aid for JSPS fellow 16J40073 (for T.M.-I.), JSPS KAKENHI Grant Number 15KT0028 and 17H03785 (for A.M.-N.) and Japan Foundation for Applied Enzymology (for A.M.-N.). This research was supported in part by the Science and Technology Incubation Program in Advanced Region from the funding program "Creation of Innovation Center for Advanced Interdisciplinary Research Areas" from the Japan Science and Technology Agency.

**Acknowledgments:** We thank Yukiko Okuo for technical support.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

### *Article* **Common Bean (***Phaseolus vulgaris* **L.) Accumulates Most** *S***-Methylcysteine as Its** γ**-Glutamyl Dipeptid**

**Elham Saboori-Robat 1,2, Jaya Joshi 1,3,4, Aga Pajak 1, Mahmood Solouki 2, Motahhareh Mohsenpour 5, Justin Renaud <sup>1</sup> and Frédéric Marsolais 1,3,\***


Received: 26 March 2019; Accepted: 12 May 2019; Published: 14 May 2019

**Abstract:** The common bean (*Phaseolus vulgaris*) constitutes an excellent source of vegetable dietary protein. However, there are sub-optimal levels of the essential amino acids, methionine and cysteine. On the other hand, *P. vulgaris* accumulates large amounts of the γ-glutamyl dipeptide of *S*-methylcysteine, and lower levels of free *S*-methylcysteine and *S*-methylhomoglutathione. Past results suggest two distinct metabolite pools. Free *S*-methylcysteine levels are high at the beginning of seed development and decline at mid-maturation, while there is a biphasic accumulation of γ-glutamyl-*S*-methylcysteine, at early cotyledon and maturation stages. A possible model involves the formation of *S*-methylcysteine by cysteine synthase from *O*-acetylserine and methanethiol, whereas the majority of γ-glutamyl-*S*-methylcysteine may arise from *S*-methylhomoglutathione. Metabolite profiling during development and in genotypes differing in total *S*-methylcysteine accumulation showed that γ-glutamyl-*S*-methylcysteine accounts for most of the total *S*-methylcysteine in mature seed. Profiling of transcripts for candidate biosynthetic genes indicated that *BSAS4;1* expression is correlated with both the developmental timing and levels of free *S*-methylcysteine accumulated, while homoglutathione synthetase (*hGS*) expression was correlated with the levels of γ-glutamyl-*S*-methylcysteine. Analysis of *S*-methylated phytochelatins by liquid chromatography and high resolution tandem mass spectrometry revealed only small amounts of homophytochelatin-2 with a single *S*-methylcysteine. The mitochondrial localization of phytochelatin synthase 2—predominant in seed, determined by confocal microscopy of a fusion with the yellow fluorescent protein—and its spatial separation from *S*-methylhomoglutathione may explain the lack of significant accumulation of *S*-methylated phytochelatins.

**Keywords:** *Phaseolus vulgaris*; common bean; *S*-methylcysteine; homoglutathione; phytochelatin synthase; cysteine; methionine

### **1. Introduction**

The common bean (*Phaseolus vulgaris* L.) is an important source of protein, dietary fiber, complex carbohydrates, vitamins, minerals and phenolic compounds [1–5]. However, its nutritional quality is restricted by a low concentration of the essential sulfur amino acids, methionine and cysteine. A large number of studies have focused on improving sulfur-containing amino acids in crops by transgenic development [6–10], synthetic protein synthesis [11] or traditional breeding [12]. Major seed proteins present in the common bean, including the 7S globulin phaseolin and lectin phytohaemagglutinin, have a low concentration of methionine and cysteine. On the other hand, the common bean accumulates non-protein sulfur amino acid derivatives such as γ–glutamyl-*S*-methylcysteine [13,14], *S*-methylcysteine [15–17] and *S*-methylhomoglutathione [18].

Two genetically related lines of the common bean, SARC1 and SMARC1N-PN1 differ in their composition of major storage proteins [19]. SMARC1N-PN1 is deficient in phaseolin and major lectins, through introgressions from *Phaseolus coccineus* and Great Northern 1140, respectively. SARC1 contains the lectin arcelin-1 introduced from a wild accession. SMARC1N-PN1 has an increased concentration of methionine and cysteine, by 10 and 70%, respectively. This increase occurs largely at the expense of total *S*-methylcysteine measured after acid hydrolysis, which is reduced by 70% [20]. This non-protein amino acid cannot replace methionine or cysteine in the diet [21]. Shifting sulfur from the non-protein amino acid pool to methionine and cysteine could be an effective strategy for protein quality improvement.

The biosynthesis of *S*-methylcysteine likely intersects with sulfur metabolism, particularly of cysteine. Sulfur is an essential macronutrient which plays a significant role in plant metabolism, increases yield and gives rise to the sulfur amino acids cysteine and methionine [22]. The most abundant environmental source of sulfur is sulfate (SO4 2-). Utilizing this essential nutrient requires a series of steps for incorporation into metabolically active forms. This includes uptake of sulfate from the environment, reduction to sulfide and synthesis of cysteine [23–26]. Delivery of adequate sulfur to seed tissues is needed for maximizing yield and to improve protein quality [22]. During cysteine biosynthesis, several enzymes are active in developing seeds of the common bean (Figure 1) [18,27]. Serine acetyltransferase catalyzes the conversion of serine to *O*-acetylserine using acetyl-CoA [28,29]. Cysteine synthase is part of the β-substituted alanine synthase (BSAS) family, along with enzymes that use cysteine and cyanide to produce β-cyanoalanine [30]. One fate of cysteine is homoglutathione that is formed via a two-step process [31,32]. γ-Glutamylcysteine is synthesized from cysteine by glutamate–cysteine ligase, and homoglutathione from γ-glutamylcysteine by homoglutathione synthetase. Another fate of sulfur is to form homophytochelatins, through the reaction of phytochelatin synthase with homoglutathione as its substrate. Phytochelatins are cysteine-rich polypeptides that chelate toxic metals [33,34].

From past studies, a model emerges for possible pathways of *S*-methylcysteine biosynthesis. There appears to be two different metabolite pools, with a different pattern of temporal accumulation. Free *S*-methylcysteine concentration is relatively high at early developmental stages, and rapidly declines at mid-maturation, whereas γ–glutamyl-*S*-methylcysteine rapidly accumulates during the early cotyledon and maturation stages [35]. *BSAS4;1* represents the dominant cytosolic cysteine synthase expressed in developing seeds [36]. As can be inferred from data in Arabidopsis [37], this enzyme might be involved in the condensation of *O*-acetylserine and methanethiol, produced by methionine γ-lyase, to form *S*-methylcysteine (Figure 1). The presence of *S*-methylhomoglutathione suggests that a pathway similar to that of the alk(en)yl sulfoxides in *Allium* [38] might be involved in the formation of γ–glutamyl-*S*-methylcysteine in *P. vulgaris*. Since homoglutathione biosynthesis takes place in plastids, such a biosynthetic mechanism would ensure an absence of interference with the cytosolic pathway of cysteine biosynthesis, predominant in seed [39,40]. This hypothesis is consistent with the depletion of *O*-acetylserine in SMARC1N-PN1, associated with increased cysteine concentration [27].

In the present study, the different forms of *S*-methylcysteine and its possible precursors, including homoglutathione and *S*-methylhomoglutathione, were profiled during seed development and between genotypes that differ in total *S*-methylcysteine concentration. The relationship between metabolite levels and transcript levels of several candidate genes, including *BSAS4;1*, glutamate–cysteine ligase (*GCL1*), homoglutathione synthetase (*hGS*) and phytochelatin synthase (*PCS2*) was evaluated. The subcellular localization of PCS2 was determined and the possible presence of *S*-methylated phytochelatins analyzed

by liquid chromatography and tandem mass spectrometry (MS/MS). The results of these experiments provide further insight into *S*-methylcysteine biosynthesis in *P. vulgaris*.

**Figure 1.** Possible biosynthetic pathway of sulfur amino acids in seed of the common bean. Solid arrows indicate steps taking place in seeds based on gene expression analysis. Multiple arrows refer to multiple steps. Broken arrows represent hypothetical steps. Metabolites in boxes are related to *S*-methylcysteine and were profiled in this study. The predominant pathway of cysteine biosynthesis in seed is cytosolic and *BSAS4;1* is the main cytosolic cysteine synthase expressed in seed. Formation of free *S*-methylcysteine by cysteine synthase is inferred from data in Arabidopsis. The presence of *S*-methylhomoglutathione suggests a pathway similar to that of the *S*-alk(enyl) sulfoxides in *Allium* leading to the formation of γ–glutamyl-*S*-methylcysteine (see text for details). OAS: *O*-acetylserine; γ–Glu-Cys, γ-glutamylcysteine; γ–Glu-*S*-methylCys, γ–glutamyl-*S*-methylcysteine; *S*-methyl-hGSH, *S*-methylhomoglutathione; BSAS4;1, β-substituted alanine synthase 4;1; PCS2, phytochelatin synthase 2; GCL1, glutamate–cysteine ligase 1; hGS, homoglutathione synthetase; MGL, methionine γ-lyase.

### **2. Results**

### *2.1. Analysis of Sulfur Metabolite Profiles During Seed Development*

To obtain more information on the accumulation of the different forms of *S*-methylcysteine and its precursors, free amino acids were profiled at seven developmental stages in BAT93 seed by high pressure liquid chromatography (HPLC) after derivatization with 3-mercaptopropionic acid and *O*-phthalaldehyde (Table 1). Developmental stages are designated after Walbot et al. [41]. Stages IV–early cotyledon to VI–early maturation are characterized by the presence of storage protein transcripts, while storage proteins accumulate from stages V–mid-cotyledon to VII–mid-maturation [42]. Stage VI–early maturation is marked by a decrease in photosynthetic capacity, with white cotyledons

by stage VII–mid-maturation. Amino acids had been profiled previously using a different methodology involving derivatization with phenyl isothiocyanate [35]. This time, additional sulfur metabolites were quantified, namely homoglutathione and *S*-methylhomoglutathione, as possible precursors to γ-glutamyl-*S*-methylcysteine. Attempts to measure the homoglutathione precursor, γ-glutamyl-cysteine, were unsuccessful. Its levels were too low for accurate quantification using the present method. Accumulation of γ-glutamyl-*S*-methylcysteine followed a biphasic curve, as previously observed, with a steady rise from stage IV–early cotyledon until stage VI–early maturation, followed by a lag, and resumption of accumulation at stage VIII–late maturation. The levels of free *S*-methylcysteine were high at the first two stages of seed development, followed by a rapid decline during the late cotyledon and maturation stages. Concentrations of *S*-methylhomoglutathione were also higher at the beginning of seed development, when γ-glutamyl-*S*-methylcysteine accumulation is most rapid. Concentrations of homoglutathione were in the same range as those of *S*-methylhomoglutathione.



Values presented are in nmol per mg seed weight; average ± standard deviation; *n* = 3. hGSH: homoglutathione; γ-Glu-*S*-methylCys: γ-glutamyl-*S*-methylcysteine; *S*-methylhGSH: *S*-methylhomoglutathione; *S*-methylCys: *S*-methylcysteine.

### *2.2. Di*ff*erences in Sulfur Amino Acid Concentrations between SARC1 and SMARC1N-PN1 under Sulfate Su*ffi*cient Conditions*

The same sulfur metabolites were quantified at five developmental stages between SARC1 and SMARC1N-PN1 under defined, sulfate sufficient conditions. Free amino acids had been profiled before in SARC1 and SMARC1N-PN1, however, the levels of homoglutathione and *S*-methylhomoglutathione had not been determined [27]. The work by Pandurangan et al. [43] indicated that 2 mM is a suitable sulfate-sufficient concentration, at which the two genotypes accumulate different levels of total *S*-methylcysteine after hydrolysis. As expected, levels of γ-glutamyl-*S*-methylcysteine were higher in SARC1 than SMARC1N-PN1, at four out of five developmental stages (Figure 2). Similar to what was previously observed, the levels of free *S*-methylcysteine were higher in SARC1 than SMARC1N-PN1 at early developmental stages, when concentrations are most elevated. The concentration of *S*-methylhomoglutathione was higher in SMARC1N-PN1 at maturity, consistent with a reduced use of

the putative γ-glutamyl-*S*-methylcysteine precursor in this genotype. Homoglutathione concentration was higher in SARC1 at stages IV and VIII, and *S*-methylhomoglutathione concentration at stage VIII, suggesting a possible enhanced flux through these putative precursors at these developmental stages.

**Figure 2.** Quantification of sulfur metabolites at different developmental stages in SARC1 and SMARC1N-PN1. Concentration is expressed in nmol per mg seed weight; average ± standard deviation; *n* = 3. Asterisks indicate significant differences at *t*-test *p* value ≤ 0.01. *n* = 3.

### *2.3. Expression Analysis of Genes Related to S-Methylcysteine and* γ*-Glutamyl-S-methylcysteine Biosynthesis*

The expression patterns of candidate genes related with the biosynthesis or metabolism of *S*-methylcysteine or γ-glutamyl-*S*-methylcysteine, *BSAS4;1*, *GCL1*, *hGS* and *PCS2*, were examined (Figure 3). *BSAS4;1* is the predominantly expressed cytosolic cysteine synthase gene in developing seeds [36]. There are two *GCL* genes in *P. vulgaris*. *GCL2* is expressed at very low levels, whereas *GCL1* and *hGS* expression is developmentally correlated (Pearson correlation coefficient = 0.85) (visualized at https://phytozome.jgi.doe.gov) [44]. Expression of the two glutathione synthetase (*GS*) genes is marginal, which explains the low level of accumulation of glutathione in *P. vulgaris*. Among two *PCS* genes, expression of *PCS1* was very low. Attempts to detect its expression by reverse transcription quantitative polymerase chain reaction (RT-qPCR) were unsuccessful. Expression of *BSAS4;1* was higher in SARC1 at the first developmental stage, which correlates with the higher levels of free *S*-methylcysteine (Figure 3). There was also a correlation between the levels of *BSAS4;1* transcripts and free *S*-methylcysteine during development (Pearson correlation coefficient = 0.83 in SARC1 and 0.96 in SMARC1N-PN1). Expression of *hGS* was significantly higher in SARC1 at three out of four developmental stages and *GCL1* at two developmental stages. This correlates with the higher levels of γ-glutamyl-*S*-methylcysteine in this genotype. *PCS2* transcript levels were higher in SMARC1N-PN1 at stage VI, opposite to what was observed for *GCL1* and *hGS*.

*Plants* **2019**, *8*, 126

**Figure 3.** Relative expression of transcripts at different developmental stages in SARC1 and SMARC1N-PN1 determined by RT-qPCR. Average ± standard deviation. Asterisks indicate significant differences at t-test *p* value ≤ 0.02. *n* = 3.

### *2.4. Subcellular Localization of PCS2*

*PCS2* is the major phytochelatin synthase gene expressed in developing seed. In vitro, *S*-methylglutathione can be used as substrate by phytochelatin synthase, in place of the metal thiolate complex with glutathione [45]. The subcellular localization of *PCS2* may therefore determine whether *S*-methylated phytochelatins can accumulate in seed. While analyzing the *PCS2* sequence from BAT93, a polymorphism specific to this genotype was uncovered which affects the length of the predicted PCS2 protein (Figure 4) [46]. This polymorphism was confirmed by RT-PCR and DNA sequencing. There is an insertion of a cytosine after position 109 downstream from the first start codon, as compared with the sequence from SARC1, SMARC1N-PN1 and the reference genome (accession G19833) [47]. The polymorphism results in a frameshift, such that PCS2 may only be translated from a downstream, alternative start codon, resulting in a shorter protein of 464 amino acid residues as compared with the longer PCS2 of 501 residues.

cDNAs encoding the long and short versions of *PCS2* were cloned from SARC1 and constructs were made to express C-terminal yellow fluorescent protein (YFP) fusions transiently in *Nicotiana benthamiana* epidermal cells. Figure 5 shows representative results obtained with the longer version of the protein. When PCS2-YFP was co-expressed with a CFP-tagged mitochondrial marker protein, PCS2-YFP was co-localized with the marker to the mitochondria. Similar results were obtained with the shorter version of the protein.

*Plants* **2019**, *8*, 126

**Figure 4.** Naturally occurring variant of *PCS2* in BAT93. (**a**) Intron–exon structure of the BAT93 *PCS2* gene. The length of introns and exons is indicated starting from the first translation initiation codon and ending at the stop codon. (**b**) The gene gives rise to two open reading frames, due to the insertion of a cytosine at position 110 of the coding sequence (CDS), which results in a premature stop codon. Corresponding positions in the cDNA with respect to the first initiation codon is indicated. ORF1 encodes a predicted polypeptide of 71 amino acids. (**c**) Due to the insertion, *PCS2* encoded in BAT93 represents a shorter form translated from an alternative, downstream start codon as compared with *PCS2* encoded by SARC1, SMARC1N-PN1 and the reference bean genome, G19833. Pfam domains present in the phytochelatin synthase sequence are indicated.

**Figure 5.** Subcellular localization of PCS2. (**a**) YFP-tagged PCS2; (**b**) CFP-tagged mitochondrial marker (Mt-CFP); (**c**) Co-localization of PCS2 with Mt-CFP. YFP: Yellow fluorescent protein; CFP: Cyan fluorescent protein.

### *2.5. Analysis of S-Methylated Phytochelatins*

To determine whether *S*-methylated phytochelatins could constitute a significant sink for *S*-methylcysteine, a systematic analysis of mature seed extracts from BAT93, SARC1 and SMARC1N-PN1 was performed by liquid chromatography and MS/MS. Similar results were obtained for the three genotypes. There are 12 distinct phytochelatins and homophytochelatins with 2–7 repeat units. However, allowing for the possibility that phytochelatins and homophytochelatins may incorporate variable numbers of *S*-methylcysteines instead of cysteines increases this number to 28 possible phytochelatins, homophytochelatins and *S*-methylated analogues (Table S1). The full MS data was screened for the theoretical *m*/*z* of these compounds (< 3 ppm). When putatively detected, the profiles were scrutinized for the presence of the 34S isotope and MS/MS was performed.

*Plants* **2019**, *8*, 126

In these extracts, the most abundant compound based on relative peak areas was γ-glutamyl-*S*methylcysteine, followed by homoglutathione and *S*-methylhomoglutathione. γ-Glutamylcysteine, *S*-methylglutathione and glutathione were present at lower concentrations. Homophytochelatin-2 and *S*-methylhomophytochelatin-2 with a single *S*-methylcysteine were detected (Figure 5). Their concentration was similar and in the same range as that of glutathione. Phytochelatin-2 was not detected (Figure 6a). A phytochelatin-2 that contains a single *S*-methylcysteine residue is isobaric with homophytochelatin-2 which contains an alanine residue in place of glycine and would not be distinguishable by high resolution MS. However, homophytochelatin and phytochelatin can be distinguished by their MS/MS product ions. Upon MS/MS, phytochelatins and homophytochelatins yield *m*/*z* 179.0486 and 193.0648 product ions, respectively. Within the analyzed samples, homophytochelatin-2 was detected and distinguished from *S*-methylphytochelatin-2 by observing this product ion (Figure 6b). Additionally, *S*-methylhomophytochelatin-2 with a single *S*-methyl group was detected with slightly more retention than homophytochelatin-2, as is expected by the additional methyl group (Figure 6c). Although a standard of *S*-methylhomophytochelatin-2 with two *S*-methyl cysteines was utilized, this compound was not detected in the seed extracts. No larger phytochelatin oligomers (<7) were detected within the samples by high resolution MS. Based on its low relative abundance, *S*-methylhomophytochelatin does not appear to constitute a major sink for *S*-methylcysteine.

**Figure 6.** MS/MS chromatograms for monitoring (**a**) phytochelatin-2 (PC2); (**b**) homophytochelatin-2 (hPC2) and (**c**) *S*-methylhomophytochelatin-2 with a single *S*-methylcysteine (*S*-methyl-hPC2).

### **3. Discussion**

### *3.1. Most of the S-Methylcysteine Accumulates as* γ*-Glutamyl-S-methylcysteine in P. vulgaris Seed*

The present study revisited the quantification of γ-glutamyl-*S*-methylcysteine in seed. Taylor et al. [20] reported that γ-glutamyl-*S*-methylcysteine accounted for only approximately 35% of total *S*-methylcysteine. Here, the final levels of γ-glutamyl-*S*-methylcysteine were about 3-fold higher than previously reported [14,35], in line with the concentration of total *S*-methylcysteine, measured after acid hydrolysis of mature seed flour, ranging from 14 to 35 nmol per mg seed weight [15,17,20]. We conclude that γ-glutamyl-*S*-methylcysteine accounts for most of the *S*-methylcysteine accumulated in mature seed. Giada et al. [14] determined that the average concentration of γ-glutamyl-*S*-methylcysteine was equal to 11 nmol per mg, with free *S*-methylcysteine accounting for the balance of the remaining 20%

of total *S*-methylcysteine measured after acid hydrolysis. In the present study, a lower concentration of free *S*-methylcysteine was measured. The higher levels of free *S*-methylcysteine measured by Giada et al. [12] may have been due to partial hydrolysis of the dipeptide during extraction, or in vivo, such as during seed storage. The difference in γ-glutamyl-*S*-methylcysteine levels between BAT93 and SARC1 suggests that there may be substantial genetic variability for the concentration of this metabolite (Table 1 and Figure 2). In future, it may be useful to quantify γ-glutamyl-*S*-methylcysteine or total *S*-methylcysteine in a wide range of *P. vulgaris* accessions or cultivars.

### *3.2. The Concentration of Homoglutathione or S-Methylhomoglutathione does not Appear to Limit the Accumulation of* γ*-Glutamyl-S-Methylcysteine*

*S*-Methylhomoglutathione concentration measured in mature seed of BAT93 in the present study was slightly higher than previously reported [18] and similar to that in *Vigna radiata* seeds [13]. Quantification of homoglutathione and *S*-methylhomoglutathione at different time points during seed development in SARC1 and SMARC1N-PN1 did not reveal major fluctuations with respect to the different levels of accumulation of the end-product, γ-glutamyl-*S*-methylcysteine (Figure 2). This is in contrast with the cysteine precursor, *O*-acetylserine, which was shown to be depleted in SMARC1N-PN1, in relation with the higher concentration of total cysteine in this genotype [27]. In BAT93, the decrease in *S*-methylhomoglutathione at early stages of seed development paralleled a rapid increase in γ-glutamyl-*S*-methylcysteine levels (Table 1).

### *3.3. Transcript Expression of BSAS4;1 and hGS is Correlated with the Accumulation of Free S-Methylcysteine and* γ*-Glutamyl-S-methylcysteine, Respectively*

The product of *BSAS4;1* is presumed to be directly involved in the formation of free *S*-methylcysteine. The developmental correlation between *BSAS4*;*1* transcript levels and free *S*-methylcysteine concentration, observed in either SARC1 or SMARC1N-PN1 (Figures 2 and 3), takes its meaning in this context. The positive genotypic correlation, observed at an early time point, when *S*-methylcysteine is at its highest levels, further implicates *BSAS4*;*1* as a plausible candidate gene (Figures 2 and 3). The higher levels of *hGS* transcript in SARC1 as compared with SMARC1N-PN1 at three out of four developmental stages (Figure 3) supports the idea that flux through homoglutathione synthetase may control, at least in part, γ-glutamyl-*S*-methylcysteine accumulation.

### *3.4. Mitochondrial Localization of PCS2 Prevents the Accumulation of S-methylated Phytochelatins*

The presence of *S*-methylhomoglutathione throughout seed development raises the question of whether *S*-methylphytochelatins can accumulate in *P.* vulgaris. Analysis of *PCS2*, the major phytochelatin synthase gene expressed in seed, revealed a polymorphism in BAT93 which would result in alternative translation initiation at a downstream start codon (Figure 4). Determination of subcellular localization by confocal microscopy demonstrated that both variants are targeted to mitochondria (Figure 5). Information on the subcellular localization of plant phytochelatin synthases is relatively limited. Arabidopsis PCS1 was shown to be present in the cytosol [48], and rice PCS1 and PCS2 were also reported to be cytosolic [49]. In the yeast *Schizosaccharomyces pombe*, phytochelatin synthase is localized in mitochondria [50]. This is logical, given that heavy metal toxicity targets mitochondrial respiration [51]. A systematic analysis of *S*-methylated phytochelatins in seed extracts found *S*-methylhomophytochelatin with a single *S*-methylcysteine, at low levels (Figure 6 and Table S1). The present results suggest that the localization of PCS2 in mitochondria ensures that the formation of phytochelatins does not interfere with the accumulation of γ-glutamyl-*S*-methycysteine.

In conclusion, our results indicate that most of the *S*-methylcysteine accumulates as γ-glutamyl-*S*-methylcysteine in mature seed. Analysis of metabolite profiles and quantitative RT-PCR data for transcripts of candidate genes of *S*-methylcysteine metabolism supports the hypothesis that expression of *BSAS4;1*, encoding the major cytosolic synthase in seed, may regulate the accumulation of free *S*-methylcysteine, whereas expression of *hGS* may regulate the accumulation of γ-glutamyl-*S*-methylcysteine, through the provision of homoglutathione and *S*-methylhomoglutathione. The mitochondrial localization of PCS2, the major phytochelatin synthase expressed in seed, is a likely explanation for the lack of substantial accumulation of *S*-methylated homophytochelatins.

### **4. Materials and Methods**

### *4.1. Plant Materials and Growth Conditions*

Three genotypes of the common bean (*Phaseolus vulgaris* L.), SARC1, SMARC1N-PN1 and BAT93 were used to evaluate sulfur metabolite profiles. Seeds were sown in small trays containing vermiculite. Ten-day-old seedlings were transplanted to a bigger pot measuring 17 cm × 20 cm containing sand, perlite, and vermiculite in a 2:1:1 ratio. SARC1 and SMARC1N-PN1 plants were grown under sulfate sufficient conditions as described in previous works [43,52]. The sulfate solution included 0.2 mM K2SO4 and 1.8 mM MgSO4 with other nutrients as follows: 4.5 mM Ca(NO3)2, 1.7 mM K2HPO4, 4 μM MnSO4.H2O, 5 μM H3BO3, 10 μM FeEDTA, 0.25 μM CuSO4.5H2O, 1 μM ZnSO4.7H2O, and 0.2 μM Na2MoO4.2H2O. The BAT93 genotype was grown as previously described [35]. The pots used in the study were placed in a randomized block design with 15 plants per genotype. Each sample consisted of three biological replicates. A biological replicate consisted of a pool of 10 seeds collected randomly from 15 plants per genotype. Plants were grown in a greenhouse with 16 h light (300–400 μmol photons m−<sup>2</sup> s<sup>−</sup>1) and 8 h dark with a temperature cycling between 18 and 24 ◦C.

### *4.2. Extraction and Quantification of Free Amino Acids*

The frozen seeds in liquid nitrogen were ground to a fine powder using a mortar and pestle. Replicate samples consisted of independent pools of ten seeds of which 100 mg were used for extraction. Sample extraction was carried out in ethanol/water (70:30), optimal for sulfur containing γ-glutamyl dipeptides [20]. Standards for γ-glutamylcysteine, γ-glutamyl-*S*-methylcysteine, *S*-methylhomoglutathione, homoglutathione and *S*-methylhomophytochelatin-2 with two *S*-methylcysteines were from Bachem (Torrance, CA, USA). Homophytochelatin-2 and phytochelatin-3 standards were from Anaspec (Fremont, CA, USA). *S*-Methylglutathione was from Millipore Sigma (Oakville, ON, Canada). Quantification of free amino acids was performed after derivatization with *O*-phthalaldehyde and mercaptopropionic acid using an Agilent 1260 Infinity HPLC system (Mississauga, ON, Canada) as described in Jafari et al. [53].

### *4.3. RNA Extraction and Quantitative RT-PCR*

Sequence analyses were performed using *Phaseolus vulgaris* v2.1, DOE-JGI and USDA-NIFA (http://phytozome.jgi.doe.gov/). Total RNA from the developmental seed samples was extracted using a modified lithium chloride method [54]. RNA was quantified with a NanoDrop 1000 (Thermo Fisher Scientific, https://www.thermofisher.com) and its quality evaluated from A260/A280 ratio. DNase I was used to remove DNA contamination that may have happened during the RNA extraction (Thermo Fisher Scientific). RNA quality was evaluated prior to cDNA synthesis by using gel electrophoresis on a 1% (w/v) agarose gel. cDNA synthesis and PCR procedures were performed using Thermoscript RT-PCR System (Thermo Fisher Scientific) and SsoFast EvaGreen Supermix (Bio-Rad Laboratories, Mississauga, ON, Canada), respectively. Primers used for RT-qPCR are listed in Table 2. Reactions contained 2 μL of cDNA diluted 5-fold, primers at a concentration of 0.5 μM and 5 μL SsoFast EvaGreen Supermix in a final volume of 10 μL. Samples were run in Hard-Shell 96-well clear PCR plates (Bio-Rad Laboratories). In each plate, three biological replicates, with three technical replicates per biological replicate and controls without template were run for developmental seed samples. The PCR program consisted in an initial step of 2 min at 95 ◦C, followed by 35 cycles of 30 s at 94 ◦C and 30 s at 60 ◦C. CFX Maestro software was used to analyze the RT-qPCR data. After completion of the reactions, the threshold fluorescence (Cq) value for each reaction was calculated. All data were normalized using the expression of the ubiquitin reference gene. The specificity of primer pairs was confirmed by melt curve

analysis in comparison with controls without template. PCR efficiency was calculated from a standard curve of Cq versus the logarithm of starting template quantity. Each assay was optimized so that the efficiency ranged between 98% and 108%, with a coefficient of determination (R2) > 0.98.


**Table 2.** Primer sequences used for RT-qPCR.

### *4.4. Cloning of PCS2 for Subcellular Localization*

The coding sequence of *PCS2* was PCR amplified using attB1 and attB2 site-containing Gateway primers from SARC1 cDNA. For the full-length version, primers were, PVPCS2-ATTB1YFPF, 5'-GGGGACAAGTTTGTACAAAAAAGCAGGCTTCATGTGCATGGCGAACCCAG-3' and PVPCS2- ATTB1YFPR, 5'-GGGGACCACTTTGTACAAGAAAGCTGGGTTCCGCTGCACAGTCCAGATTGCT-3'. For the short variant using the alternative downstream start codon, the forward primer was PCS2-ATTB1YFPF, 5'-GGGGACAAGTTTGTACAAAAAAGCAGGCTTCATGGAAGCCTTCTTCAAG C-3'. The PCR products were inserted into the entry vector pDONR-Zeo (Thermo Fisher Scientific). The integrity of the PCR fragments was confirmed with Sanger sequencing. Using Gateway technology, LR recombination reactions were performed with entry clones pDONR-Zeo-PCS2fl and pDONR-Zeo-PCS2tr and destination vector pEarleyGate101 [55]. The final expression constructs (pEG101-PCS2fl and pEG101-PCS2tr) were transformed into *Agrobacterium tumefaciens* strain GV3101.

### *4.5. Plant Transformation and Confocal Observations*

*Nicotiana benthamiana* plants were grown for 6 weeks and used for transient expression. Plants were grown in a growth chamber at 22 ◦C with a 16 h photoperiod (110 μmol photons m−<sup>2</sup> s<sup>−</sup>1). Plants were always watered with the water soluble fertilizer (N:P:K = 20:8:20) at 0.25 g/L (Plant Products, Brampton, ON, Canada). *Agrobacterium tumefaciens* cultures were grown to an optical density at 600 nm (OD600) of 0.5–0.8, and collected by centrifugation at 3,000 × *g* for 30 min. The pellets were resuspended in Gamborg's solution (3.2 g/L Gamborg's B5 medium and vitamins, 20 g/L sucrose, 10 mM 2-(*N*-morpholino)ethanesulfonic acid pH 5.6, 200 μM acetosyringone) to a final OD600 of 1, followed by incubation at room temperature (21 ◦C) with gentle agitation for 1 h. For co-infiltration, the mitochondrial protein (cytochrome oxidase with CFP) was mixed with YFP construct (pEG101-PCS2) in a 1:1 ratio [56]. The suspension was used for co-infiltration of the abaxial side of the leaf with a 1 mL syringe. Three to four days post infiltration, the abaxial epidermis of the leaves was observed using an OLYMPUS FV1200 Laser Scanning Microscope (https://www.olympus-lifescience.com/). A 60 × water immersion objective was used at excitation wavelengths of 514 and 458 nm. The fluorescence signals were detected using an emission spectra of 530–560 nm for YFP and 470-500 nm for CFP. Sequential Scan Tool, which records fluorescence in a sequential fashion, was used for studying co-localization of PCS2 with marker protein.

### *4.6. Analysis of S-methylated Phytochelatins*

Extraction of phytochelatins from mature seed tissue was performed according to a published method with slight modifications [57]. The mature seed samples were ground with a Kleco ball mill (Garcia Machine, Visalia, CA, USA). One hundred mg of powder was mixed with 1 mL of cold (4 ◦C) 100 mM dithiothreitol in a polypropylene centrifuge tube. The suspension was vortexed for 1 min, and then sonicated for 5 min at room temperature. The extract was precipitated by centrifugation at 15,000× *g* at 4 ◦C for 20 min. The supernatants were transferred to a polypropylene centrifuge tube

and the centrifugation repeated one more time. The supernatants were filtered with PTFE syringe filters (0.22 μm) into 2 mL amber glass HPLC vials.

The extracts were screened using a Q-Exactive Quadrupole Orbitrap mass spectrometer (Thermo Fisher Scientific), coupled to an Agilent 1290 high-performance liquid chromatography (HPLC) system with a Zorbax Eclipse Plus RRHD C18 column maintained at 35 ◦C (2.1 × 50 mm, 1.8 μm; Agilent). Mobile phase A (0.1% formic acid in LC-MS grade H2O, Thermo Fisher Scientific) began at 100% and was held for 1.25 min. Mobile phase B (0.1% formic acid in LC-MS grade acetonitrile, Thermo Fisher Scientific) was then increased to 50% over 1.75 min, and 100% over 0.5 min. Mobile phase B was maintained at 100% for 1.5 min and returned to 0% over 0.5 min. The following heated electrospray ionization (HESI) parameters were used in positive ionization mode: spray voltage, 3.9 kV; capillary temperature, 250 ◦C; probe heater temperature, 450 ◦C; sheath gas, 30 arbitrary units; auxiliary gas, 8 arbitrary units; and S-Lens RF level, 60%. High resolution, full MS was used to detect any possible phytochelatins and homophytochelatins (PC2-7) by accurate mass (Table S1), while MS/MS scans performed concurrently monitored PC2 (*m*/*z* 540 → 179.0486), homoPC2 (*m*/*z* 554 → 193.0648) and *S*-methyl-homoPC2 (*m*/*z* 568 → 193.0648) all at normalized collision energies (NCE) of 24. The full MS scans were performed at 70,000 resolution over a mass range of 100–2000 *m*/*z*; automatic gain control (AGC) target and maximum injection time (max IT) was 3 × 106 and 256 msecond respectively. The MS/MS scans were performed at 17,500 resolution AGC target and max IT were 3 × 106 and 64 msecond respectively. Data were analyzed and all theoretical masses were calculated with Xcalibur™ software.

### *4.7. Statistical Analysis*

The experiments were carried out as a factorial in a completely randomized experimental design with three replications. *t*-Test was performed using IBM SPSS® software (Armonk, NY, USA).

**Supplementary Materials:** Table S1. Monitoring of phytochelatin ions in MS/MS data.

**Author Contributions:** E.S.-R., A.P. and J.R. performed the experiments. J.J. and F.M. designed the research. M.S., M.M. and F.M. supervised E.S.-R. E.S.-R., A.P., J.R. and F.M. analyzed the data. E.S.-R., J.R. and F.M. wrote the manuscript.

**Funding:** This research was funded by Agriculture and Agri-Food Canada (project no. J-001331). E.S.-R. received funding from the Ministry of Science, Research and Technology of Iran. J.J. was the recipient of the Dr. René Roth Memorial Award during her Ph. D. studies in the Department of Biology of the University of Western Ontario.

**Acknowledgments:** We thank Mark Bernards for acting as J.J.'s co-supervisor during her Ph. D. program and Alex Molnar for help with figures.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


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